Doing Korean Kakao promotion, data integrity is replacing some active tags

existIn the Kakao user screening scenario, one change is becoming more and more obvious: relying solely on active user tags may no longer be able to filter out more suitable target groups. Especially in local promotion in South Korea, the dimension of data completeness is gradually replacing some active tags and becoming an important reference for judging the quality of accounts.

Many people will initially think that active user screening is enough, because active means that the user has usage behavior. However, after running for a period of time, you will find that although some accounts are active, the information is incomplete and the structure is unclear, and their performance in actual reach and conversion is not stable. Conversely, some users with high data integrity, even if their active frequency is not the highest, are closer to real users and are more likely to have effective interactions.

This is whyDuring Kakao promotion, the screening logic began to change.

why koreaKakao promotion depends more and more on the completeness of the information

The core reason is that the local user structure is more biased towards real usage habits.

In some areas, activity can be used as the main judgment dimension, but in South KoreaIn the Kakao ecosystem, the user data structure itself is relatively standardized, and many real users will have relatively complete data information, which naturally makes data completeness of higher reference value.

If an account's data structure is incomplete, even if it shows active behavior, it can easily be judged as a low-quality or abnormal account. In this case, only active tags are looked at, and the filtering accuracy will be reduced.

Therefore, data integrity began to shift from auxiliary judgment to pre-judgment.

What signals does data integrity include?

Data completeness is not a single dimension, but a combination of multiple basic information.

The most common one is the avatar. Whether there is an avatar and whether the avatar is real is the first level of judgment.

The second is the nickname structure, such as whether it is normal and consistent with user habits.

The other is basic information, such as whether the account number is completed.

This information alone has limited meaning, but when combined, it can form a more stable account structure judgment.

existIn Kakao user screening, this type of structural information is often more stable than a single active tag.

Why data completeness replaces some active tags

The reason is that there is room for misjudgment in active tags.

Nowadays, many accounts, even abnormal accounts, can simulate certain active behaviors, but the data structure is often more difficult to completely simulate real users.

Therefore, in some scenarios, the data integrity is closer to real user identification.

This is why more and moreKakao's screening logic will first look at the completeness of the data, and then look at the active status, not the other way around.

It’s not that the active tag isn’t important, it’s just that it’s no longer suitable to be used on its own.

When filtering Kakao users, how should data completeness and activity be matched?

A more reasonable approach is to use them in layers rather than choosing one or the other.

In the basic screening stage, you can prioritize the first round of filtering based on data integrity to eliminate obviously low-quality accounts.

At the second level, active user screening is added to determine which accounts are currently more suitable to be reached.

This combination is more stable than just looking at activity or only looking at data.

Because data integrity solves the problem of authenticity, and active tags solve the problem of immediate use, there is no conflict between the two.

More suitable for KoreaWhat is the filtering order for Kakao promotion?

From a practical perspective, a more stable sequence is usually to first perform basic account identification to ensure data availability, then make data integrity judgments, filter accounts with low-quality structures, then filter active users, and finally filter abnormal accounts.

The core of this sequence is to first determine whether the account looks like a real user, and then determine whether the user has any usage behavior.

If the order is reversed, it is easy to regard fake active accounts as high-quality data.

This is why the filter order, inKakao is becoming more and more important in promotion.

The role of Digital Planet in this type of screening process

In actual operations, many teams will use Digital Planet to firstKakao account detection and data structure identification, combined with active user filtering and abnormal account filtering, separate real users from highly available users. Digital Planet supports free trial screening test, which is more suitable for multi-dimensional combination screening, and handles data integrity, activity status and account quality in the same process.

This method is more suitable for the current situation than single-dimensional filtering.Kakao promotion environment.

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